Stock Price Trend Analysis Method Based on Change Cycle Clustering
<p>Yang Wang<sup>1</sup>, Linjie Huang<sup>2</sup>, Yidan Zheng<sup>3</sup>, Siuwa Lee<sup>4</sup>, Yuanming Fu<sup>5</sup></p> · Academic Journal of Computing & Information Science · 2021
With the continuous development of financial informatization and the continuous improvement of China's economic system, analyzing and mining financial data has become an important means to study financial problems. Compared with other industries in the financial field, stock data is easier to collect and store, and its application is more convenient. Analyzing and predicting the changing trend of the future stock market through the historical data of stocks is helpful to reduce the risk of investors and increase income. It has become a research hotspot in the financial field. Using the historical price data of domestic stocks, a method based on a clustering algorithm is proposed to analyze the periodic characteristics of stock price changes. This method can provide a basis for the prediction of stock price and the detection of trading behaviour in the stock market.